L3 acquisition: a focus on cognitive approaches

Interest in third language (L3) acquisition has increased exponentially in recent years, due to its potential to inform long-lasting debates in theoretical linguistics, language acquisition and psycholinguistics. Researchers investigating child and adult L3 acquisition have, from the very beginning, considered the many different cognitive factors that constrain and condition the initial state and development of newly acquired languages, and their models have duly evolved to incorporate insights from the most recent findings in psycholinguistics, neurolinguistics and cognitive psychology. The articles in this Special Issue of Bilingualism: Language and Cognition, in dealing with issues such as age of acquisition, attrition, relearning, cognitive economy or the reliance on different memory systems –to name a few–, provide an accurate portrayal of current inquiry in the field, and are a particularly fine example of how instrumental research in language acquisition and other cognitive domains can be to one another.

Anticipating future risk in social-ecological systems using fuzzy cognitive mapping: the case of wildfire in the Chiquitania, Bolivia

Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging due to reinforcing feedbacks between multiple drivers. We conducted semi-structured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision-making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. All scenarios showed increased wildfire risk in the event of more droughts. The ‘Hands-off’ scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production. The ‘Fire management’ scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared to the ‘Fire suppression’ scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decision-support tool and serve as a ‘boundary object’ to facilitate collaboration and integration of different forms of knowledge and perceptions of fire in the region. This approach has also the potential to support decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.